Beispiel #1
0
 def test_rots(theta):
     invVR_mats = ltool.matrix_multiply(invV_mats, R_mats(theta))
     _oris = ktool.get_invVR_mats_oris(invVR_mats)
     print('________')
     print('theta = %r' % (theta % TAU, ))
     print('b / a = %r' % (_oris, ))
     passed, error = utool.almost_eq(_oris, theta % TAU, ret_error=True)
     try:
         assert np.all(passed)
     except AssertionError as ex:
         utool.printex(ex, 'rotation unequal', key_list=['passed', 'error'])
Beispiel #2
0
 def test_rots(theta):
     invVR_mats = ltool.matrix_multiply(invV_mats, R_mats(theta))
     _oris = ktool.get_invVR_mats_oris(invVR_mats)
     print('________')
     print('theta = %r' % (theta % TAU,))
     print('b / a = %r' % (_oris,))
     passed, error = utool.almost_eq(_oris, theta % TAU, ret_error=True)
     try:
         assert np.all(passed)
     except AssertionError as ex:
         utool.printex(ex, 'rotation unequal', key_list=['passed',
                                                         'error'])
def _test_hypothesis_inliers(Aff, invVR1s_m, xy2_m, det2_m, ori2_m,
                             xy_thresh_sqrd, scale_thresh_sqrd, ori_thresh):
    """
    Critical section code. Inner loop of _test_hypothesis_inliers

    CommandLine:
        python -m vtool.spatial_verification --test-_test_hypothesis_inliers

    Example:
        >>> # ENABLE_DOCTEST
        >>> from vtool.spatial_verification import *  # NOQA
        >>> from vtool.spatial_verification import _test_hypothesis_inliers  # NOQA
        >>> import vtool.tests.dummy as dummy
        >>> import vtool.keypoint as ktool
        >>> _kw1 = dict(seed=12, damping=1.2, wh_stride=(30, 30))
        >>> _kw2 = dict(seed=24, damping=1.6, wh_stride=(30, 30))
        >>> kpts1 = dummy.perterbed_grid_kpts(**_kw1).astype(np.float64)
        >>> kpts2 = dummy.perterbed_grid_kpts(**_kw2).astype(np.float64)
        >>> fm = dummy.make_dummy_fm(len(kpts1)).astype(np.int32)
        >>> kpts1_m = kpts1[fm.T[0]]
        >>> kpts2_m = kpts2[fm.T[1]]
        >>> xy_thresh_sqrd = np.float64(.009) ** 2
        >>> scale_thresh_sqrd = np.float64(2)
        >>> ori_thresh = np.float64(TAU / 4)
        >>> # Get keypoints to project in matrix form
        >>> #invVR1s_m = ktool.get_invV_mats(kpts1_m, with_trans=True, with_ori=True)
        >>> #print(invVR1s_m[0])
        >>> invVR1s_m = ktool.get_invVR_mats3x3(kpts1_m)
        >>> RV1s_m = ktool.get_RV_mats_3x3(kpts1_m)
        >>> invVR2s_m = ktool.get_invVR_mats3x3(kpts2_m)
        >>> # The transform from kp1 to kp2 is given as:
        >>> Aff_mats = matrix_multiply(invVR2s_m, RV1s_m)
        >>> Aff = Aff_mats[0]
        >>> # Get components to test projects against
        >>> xy2_m  = ktool.get_invVR_mats_xys(invVR2s_m)
        >>> det2_m = ktool.get_sqrd_scales(kpts2_m)
        >>> ori2_m = ktool.get_invVR_mats_oris(invVR2s_m)
        >>> output = _test_hypothesis_inliers(Aff, invVR1s_m, xy2_m, det2_m, ori2_m, xy_thresh_sqrd, scale_thresh_sqrd, ori_thresh)
        >>> result = ut.hashstr(output)
        >>> print(result)
        +%q&%je52nlyli5&

    Timeit:
        %timeit xy_err < xy_thresh_sqrd
        %timeit np.less(xy_err, xy_thresh_sqrd)
    """
    # Map keypoints from image 1 onto image 2
    invVR1s_mt = matrix_multiply(Aff, invVR1s_m)

    # Get projection components
    _xy1_mt = ktool.get_invVR_mats_xys(invVR1s_mt)
    _det1_mt = ktool.get_invVR_mats_sqrd_scale(invVR1s_mt)
    _ori1_mt = ktool.get_invVR_mats_oris(invVR1s_mt)
    ## Check for projection errors
    xy_err = dtool.L2_sqrd(xy2_m.T, _xy1_mt.T, dtype=SV_DTYPE)
    scale_err = dtool.det_distance(_det1_mt, det2_m)
    ori_err = dtool.ori_distance(_ori1_mt, ori2_m)

    # Mark keypoints which are inliers to this hypothosis
    xy_inliers_flag = np.less(xy_err, xy_thresh_sqrd)
    scale_inliers_flag = np.less(scale_err, scale_thresh_sqrd)
    ori_inliers_flag = np.less(ori_err, ori_thresh)
    #np.logical_and(xy_inliers_flag, scale_inliers_flag)
    # TODO Add uniqueness of matches constraint
    #hypo_inliers_flag = np.empty(xy_inliers_flag.size, dtype=np.bool)
    hypo_inliers_flag = xy_inliers_flag  # Try to re-use memory
    np.logical_and(hypo_inliers_flag, ori_inliers_flag, out=hypo_inliers_flag)
    np.logical_and(hypo_inliers_flag,
                   scale_inliers_flag,
                   out=hypo_inliers_flag)
    #hypo_inliers_flag = np.logical_and.reduce(
    #    [xy_inliers_flag, ori_inliers_flag, scale_inliers_flag])
    # this is also slower
    hypo_inliers = np.where(hypo_inliers_flag)[0]
    hypo_errors = (xy_err, ori_err, scale_err)
    return hypo_inliers, hypo_errors
Beispiel #4
0
def _test_hypothesis_inliers(Aff, invVR1s_m, xy2_m, det2_m, ori2_m,
                             xy_thresh_sqrd, scale_thresh_sqrd, ori_thresh):
    """
    Critical section code. Inner loop of _test_hypothesis_inliers

    CommandLine:
        python -m vtool.spatial_verification --test-_test_hypothesis_inliers

    Example:
        >>> # ENABLE_DOCTEST
        >>> from vtool.spatial_verification import *  # NOQA
        >>> from vtool.spatial_verification import _test_hypothesis_inliers  # NOQA
        >>> import vtool.tests.dummy as dummy
        >>> import vtool.keypoint as ktool
        >>> _kw1 = dict(seed=12, damping=1.2, wh_stride=(30, 30))
        >>> _kw2 = dict(seed=24, damping=1.6, wh_stride=(30, 30))
        >>> kpts1 = dummy.perterbed_grid_kpts(**_kw1).astype(np.float64)
        >>> kpts2 = dummy.perterbed_grid_kpts(**_kw2).astype(np.float64)
        >>> fm = dummy.make_dummy_fm(len(kpts1)).astype(np.int32)
        >>> kpts1_m = kpts1[fm.T[0]]
        >>> kpts2_m = kpts2[fm.T[1]]
        >>> xy_thresh_sqrd = np.float64(.009) ** 2
        >>> scale_thresh_sqrd = np.float64(2)
        >>> ori_thresh = np.float64(TAU / 4)
        >>> # Get keypoints to project in matrix form
        >>> #invVR1s_m = ktool.get_invV_mats(kpts1_m, with_trans=True, with_ori=True)
        >>> #print(invVR1s_m[0])
        >>> invVR1s_m = ktool.get_invVR_mats3x3(kpts1_m)
        >>> RV1s_m = ktool.get_RV_mats_3x3(kpts1_m)
        >>> invVR2s_m = ktool.get_invVR_mats3x3(kpts2_m)
        >>> # The transform from kp1 to kp2 is given as:
        >>> Aff_mats = matrix_multiply(invVR2s_m, RV1s_m)
        >>> Aff = Aff_mats[0]
        >>> # Get components to test projects against
        >>> xy2_m  = ktool.get_invVR_mats_xys(invVR2s_m)
        >>> det2_m = ktool.get_sqrd_scales(kpts2_m)
        >>> ori2_m = ktool.get_invVR_mats_oris(invVR2s_m)
        >>> output = _test_hypothesis_inliers(Aff, invVR1s_m, xy2_m, det2_m, ori2_m, xy_thresh_sqrd, scale_thresh_sqrd, ori_thresh)
        >>> result = ut.hashstr(output)
        >>> print(result)
        +%q&%je52nlyli5&

    Timeit:
        %timeit xy_err < xy_thresh_sqrd
        %timeit np.less(xy_err, xy_thresh_sqrd)
    """
    # Map keypoints from image 1 onto image 2
    invVR1s_mt = matrix_multiply(Aff, invVR1s_m)

    # Get projection components
    _xy1_mt   = ktool.get_invVR_mats_xys(invVR1s_mt)
    _det1_mt  = ktool.get_invVR_mats_sqrd_scale(invVR1s_mt)
    _ori1_mt  = ktool.get_invVR_mats_oris(invVR1s_mt)
    ## Check for projection errors
    xy_err    = dtool.L2_sqrd(xy2_m.T, _xy1_mt.T, dtype=SV_DTYPE)
    scale_err = dtool.det_distance(_det1_mt, det2_m)
    ori_err   = dtool.ori_distance(_ori1_mt, ori2_m)

    # Mark keypoints which are inliers to this hypothosis
    xy_inliers_flag    = np.less(xy_err, xy_thresh_sqrd)
    scale_inliers_flag = np.less(scale_err, scale_thresh_sqrd)
    ori_inliers_flag   = np.less(ori_err, ori_thresh)
    #np.logical_and(xy_inliers_flag, scale_inliers_flag)
    # TODO Add uniqueness of matches constraint
    #hypo_inliers_flag = np.empty(xy_inliers_flag.size, dtype=np.bool)
    hypo_inliers_flag = xy_inliers_flag  # Try to re-use memory
    np.logical_and(hypo_inliers_flag, ori_inliers_flag, out=hypo_inliers_flag)
    np.logical_and(hypo_inliers_flag, scale_inliers_flag, out=hypo_inliers_flag)
    #hypo_inliers_flag = np.logical_and.reduce(
    #    [xy_inliers_flag, ori_inliers_flag, scale_inliers_flag])
    # this is also slower
    hypo_inliers = np.where(hypo_inliers_flag)[0]
    hypo_errors = (xy_err, ori_err, scale_err)
    return hypo_inliers, hypo_errors